Kwokwai Cheung

A new empirical model for indoor propagation prediction

In this paper, a new empirical model for indoor propagation prediction is presented. The inspiration for our model is to enhance existing empirical models for indoor propagation prediction by incorporating additional phenomena suggested by electromagnetic techniques such as the uniform theory of diffraction (UTD), but still retain the straightforwardness of the empirical approach. The advantage is that computation time for indoor propagation prediction is low without greatly compromising prediction accuracy. Comparisons of our predicted results to measurements indicate that improvements in accuracy over conventional empirical models are achieved.

A Bayesian framework for deformable pattern recognition with application to handwritten character recognition

Deformable models have recently been proposed for many pattern recognition applications due to their ability to handle large shape variations. These proposed approaches represent patterns or shapes as deformable models, which deform themselves to match with the input image, and subsequently feed the extracted information into a classifier. The three components-modeling, matching, and classification-are often treated as independent tasks. In this paper, we study how to integrate deformable models into a Bayesian framework as a unified approach for modeling, matching, and classifying shapes. Handwritten character recognition serves as a testbed for evaluating the approach. With the use of our system, recognition is invariant to affine transformation as well as other handwriting variations. In addition, no preprocessing or manual setting of hyperparameters (e.g., regularization parameter and character width) is required. Besides, issues on the incorporation of constraints on model flexibility, detection of subparts, and speed-up are investigated. Using a model set with only 23 prototypes without any discriminative training, we can achieve an accuracy of 94.7 percent with no rejection on a subset (11,791 images by 100 writers) of handwritten digits from the NIST SD-1 dataset.

On deformable models for visual pattern recognition

This paper reviews model-based methods for non-rigid shape recognition. These methods model, match and classify non-rigid shapes, which are generally problematic for conventational algorithms using rigid models. Issues including model representation, optimization criteria formulation, model matching, and classification are examined in detail with the objective to provide interested researchers a roadmap for exploring the field. This paper emphasizes on 2D deformable models. Their potential applications and future research directions, particularly on deformable pattern classification, are discussed.

A new approach to indoor propagation prediction

A new approach to indoor propagation prediction which is based on the Rayleigh-Gans approximation is proposed. The approach has been motivated by the observation that the indoor environment is different from the outdoor environment in that many of the structures within buildings are approximately the size of a wavelength making propagation prediction based on high frequency techniques not strictly applicable. In the paper details of the Rayleigh-Gans approximation are provided. Actual indoor propagation measurements are also provided to allow preliminary discussions on the accuracy of the Rayleigh-Gans approximation to be given. Comparisons with simulations of empirical and ray tracing models are also provided. The results indicate that further development would be worthwhile.<<ETX>>

Improved empirical modeling for indoor propagation prediction

An improved empirical model for indoor propagation prediction is presented. The inspiration for the model is to enhance existing empirical or statistical models so that they can take better account of propagation phenomena that are predicted by formal electromagnetic techniques such as UTD. This allows to arrive at a new empirical model with the advantages of both conventional empirical and formal electromagnetic approaches.

Measurement, characterization and modeling of the wideband indoor channel

Detailed knowledge of radio propagation inside buildings is essential for successful design of indoor communication systems. The research presented in this paper is concerned with measurement, characterization and modeling of the indoor wideband channel response in the 1.75-1.85 GHz frequency band. In order to investigate and model the wideband channel characteristics for indoor environments, time delay profile measurements have been taken inside a modern building with receiver-transmitter separations from 5-30 m. Channel characteristics such as mean excess delay, delay spread and path loss are studied. Possible relations between these parameters are also studied. Finally, a wideband model based on ray-tracing is compared to the measurement results to determine the models overall accuracy.

Competitive mixture of deformable models for pattern classification

Following the success of applying deformable models to feature extraction, a natural next step is to apply such models to pattern classification. Recently, we have cast a deformable model under a Bayesian framework for classification, giving promising results. However, deformable model methods are computationally expensive due to the required iterative optimization process. The problem is even more severe when there are a large number of models (e.g., for character recognition), because each of them has to deform and match with the input data before a final classification can be derived. In this paper, we propose to combine the deformable models into a mixture, in which the individual models compete with each other to survive the matching process during classification. Models that do not compete well are eliminated early, thus allowing substantial savings in computation. This process of competition-elimination has been applied to handwritten digit recognition in which significant speedup can be achieved without sacrificing recognition accuracy.

A bidirectional matching algorithm for deformable pattern detection with application to handwritten word retrieval

A Bayesian framework for deformable pattern classification was proposed by K.W. Cheung et al. (1998), with promising results for isolated handwritten character recognition. Its performance, however degrades significantly when it is applied to detect deformable patterns in complex scenes, where the amount of outliers due to other neighboring objects or the background is usually large. Also, the fact that the associated evidence measure does not penalize models resting on white space results in a high false alarm rate. Another Bayesian framework for deformable pattern detection is proposed. The framework possesses the intrinsic property of matching with only part of an image (segmentation) and its associated evidence measure can penalize white space implicitly. However, limited data exploration capability is the major trade-off. By properly combining the two frameworks, a new matching algorithm called bidirectional matching is proposed. This combined approach possesses the advantages of the two frameworks and gives robust results for non-rigid shape extraction. To evaluate the performance of the proposed approach, we have applied it to shape-based handwritten word retrieval. Using a subset of the bb dataset in the CEDAR database, we can achieve a recall rate of 59% and a precision rate of 43%.

The fading characteristics of distributed antennas for indoor wireless systems

Distributed antennas have been suggested as a possible method for providing reliable coverage for indoor wireless communications. One aspect of the distributed antenna system however has not been well investigated. This concerns possible interference effects (resulting in fading) between antennas within the distributed antenna. In this paper we analyze and simulate the potential effects of this fading to exactly determine whether it will play a significant role in the coverage provided by distributed antennas. We also compare our simulations to actual measurement results in the mobile telephone bands. Particular design criteria are then suggested.